Fuel is the number one expense for a trucking company outside of the truck’s driver. The commercial trucking industry in the United States spends more than $140B a year on fuel, so saving even $1 of fuel goes right to the bottom line. In an industry with razor-sharp margins, this can mean the difference between a red and a black income statement.
A digital twin models a real-world physical asset using mobile data, cloud computing, and machine learning to track chosen characteristics. The goal of digital twin modeling is to improve visibility and control to optimize performance. Lloyd Palum walks you through building a digital twin that tracks and reports fuel efficiency performance of specific commercial tractor trailers using Python and TensorFlow. You can then use the example model to track and optimize performance.
Lloyd Palum is the CTO of Vnomics, where he directs the company’s technology development associated with optimizing fuel economy in commercial trucking. Lloyd has more than 25 years of experience in both commercial and government electronics, has published a number of technical articles, and speaks frequently at industry conferences. He holds five patents in the field of software and wireless communications. Lloyd earned his MSEE from Boston University and BSEE from the University of Rochester.
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